Chen et al. (2020) introduced the concept of measuring and relieving the over-smoothing problem for graph neural networks from a topological view. Fei (2018)…
Browsing: Graph Neural Networks
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications…
The US Department of Energy’s Argonne National Laboratory is making the latest generation of Graphcore Bow IPUs available for free to scientific researchers around…
This paper proposes a new recommendation method based on iterative heterogeneous graph learning on knowledge graphs (HGKR). HGKR incorporates graph neural networks into the…
Researchers from the University of Hong Kong, the Chinese Academy of Sciences, InnoHK Centers and other institutes worldwide have developed a software-hardware system that…